We study the clinical value of some logical models with cell lines data from CellModelPassports portal and GDSC dataset. Let’s first import simulation results and drug/CRISPR screening files.
## [1] "All imports OK"
But first, is there any consistence between all these values?
We define a normalised variable based on level without any drug inhibition (i.e \(Proliferation_{normalised} = Proliferation_{withDrug} / Proliferation_{withoutDrug}\))
Some interesting points:
Here are additional plots for other targets;
For drugs we will focus on PLX (but very similar to PLX in all aspects, no particular criterion to distinguish) and AUC metric (less sensitive to extrapolation). For CRISPR screening we will focus on CC2 dataset, more balanced in CM and CRC. For output we will also focus on normalisedx Proliferation scores:
Here is the pruned version of the plot for publication:
Now we want to have a deeper understanding of these correlation relations looking at the scatter plots
Here is the version for publication:
And here is the version with table
Additional plot for p53 and PI3K:
We can have a deeper look at scatter plot with interactive settings
Here is the non-interactive reference plots
Let’s generate each column as an interactive plot, first with drugs and then with CRISPR:
And a last interactive plot to visualize the benefit of RNA addition for CRISPR prediction: